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Record W2033167284 · doi:10.2298/abs1404633s

Tiazofurin modulates lipopolysaccharide-activated microglia in vitro

2014· article· en· W2033167284 on OpenAlexaff
Danijela Savić, Irena Lavrnja, Sanja Đačić, Ivana Bjelobaba, Nadežda Nedeljković, Mirjana Stojiljković, Thomas Herdegen, Sanja Peković

Bibliographic record

VenueArchives of Biological Sciences · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsInstitute for Biological Sciences
FundersMinistarstvo Prosvete, Nauke i Tehnološkog Razvoja
KeywordsMicrogliaPharmacologyTumor necrosis factor alphaInterleukinLipopolysaccharideCytokineNitric oxideChemistryImmunologyInflammationBiologyEndocrinology

Abstract

fetched live from OpenAlex

Tiazofurin is a purine nucleoside analogue, with a broad spectrum of antitumoral and anti-inflammatory properties. In the present study, we have investigated the effect of tiazofurin on microglial inflammatory response to lipopolysaccharide in vitro. The cytotoxic effect of the drug was examined by sulforhodamine B assay. The Griess method was used to quantify nitrite production. Microglial morphology was assessed by measuring cell body size. Release of the pro-inflammatory cytokines, tumor necrosis factor-?, interleukin-1?, interleukin-6, and the anti-inflammatory cytokine interleukin- 10, were evaluated by enzyme-linked immunosorbent assay. Our data showed that tiazofurin decreased the number of activated microglia, lowered nitric oxide production and reduced the average cell surface of these cells. Tiazofurin reduced tumor necrosis factor-?, interleukin-6 and increased interleukin-10 secretion. Conversely, this drug promoted the release of interleukin-1?. Results obtained in this study indicate that TR displayed both anti- and pro-inflammatory modulation of activated microglia that could be relevant for its antitumor action within the central nervous system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.270
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2014
Admission routes1
Has abstractyes

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